Temporal consistency enhancement of depth video sequence

Abstract

Stereo matching algorithms base on image similarity to find correspondence between two images. All of the stereo matching methods suffer from lack of texture, occlusion, spontaneous noise, which would result in incorrect depth estimation. Such caused random depth errors in a video sequence would cause sporadic flickering, thus reducing the perceptive quality of the rendered 3D video. This paper proposes the consistency check of the depth values in temporal sequence to identify the instances with occlusion and noise and based on the results, correct the depth errors due to occlusion and spontaneous noise. The resultant depth values are then gone through evaluation using Newton's Law of motion. The depth values which do not comply with the Newton's Law of motion are corrected. Finally we use a bilateral filter to further smooth the video depth values.

abstract = "Stereo matching algorithms base on image similarity to find correspondence between two images. All of the stereo matching methods suffer from lack of texture, occlusion, spontaneous noise, which would result in incorrect depth estimation. Such caused random depth errors in a video sequence would cause sporadic flickering, thus reducing the perceptive quality of the rendered 3D video. This paper proposes the consistency check of the depth values in temporal sequence to identify the instances with occlusion and noise and based on the results, correct the depth errors due to occlusion and spontaneous noise. The resultant depth values are then gone through evaluation using Newton's Law of motion. The depth values which do not comply with the Newton's Law of motion are corrected. Finally we use a bilateral filter to further smooth the video depth values.",

N2 - Stereo matching algorithms base on image similarity to find correspondence between two images. All of the stereo matching methods suffer from lack of texture, occlusion, spontaneous noise, which would result in incorrect depth estimation. Such caused random depth errors in a video sequence would cause sporadic flickering, thus reducing the perceptive quality of the rendered 3D video. This paper proposes the consistency check of the depth values in temporal sequence to identify the instances with occlusion and noise and based on the results, correct the depth errors due to occlusion and spontaneous noise. The resultant depth values are then gone through evaluation using Newton's Law of motion. The depth values which do not comply with the Newton's Law of motion are corrected. Finally we use a bilateral filter to further smooth the video depth values.

AB - Stereo matching algorithms base on image similarity to find correspondence between two images. All of the stereo matching methods suffer from lack of texture, occlusion, spontaneous noise, which would result in incorrect depth estimation. Such caused random depth errors in a video sequence would cause sporadic flickering, thus reducing the perceptive quality of the rendered 3D video. This paper proposes the consistency check of the depth values in temporal sequence to identify the instances with occlusion and noise and based on the results, correct the depth errors due to occlusion and spontaneous noise. The resultant depth values are then gone through evaluation using Newton's Law of motion. The depth values which do not comply with the Newton's Law of motion are corrected. Finally we use a bilateral filter to further smooth the video depth values.